When running
from interpret import show
from interpret.perf import ROC
blackbox_perf = ROC(blackbox_model.predict_proba).explain_perf(X_test, y_test, name='Blackbox')
show(blackbox_perf)

I have the following error

RuntimeError: Could not find open port.
Consider calling interpret.set_show_addr(("127.0.0.1", 7001)) first..

Even calling the set_show_addr, I

• It would be nice to have a list of current contributors and update this list as more people add resources to this repo.

General:

• remove outdated examples from DALEX_docs
• prepare skeleton for R/Python docs

R specific:

• prepare Introductory materials to predictive models for titanic and apartments
• prepare Introductory materials to explain()
• prepare Introductory materials to predict_parts()
• prepare Introductory materials to predict_profile()
• prepar

There are several instances where the functional form is shown as
$$\beta_0 + f_1(X_1) + f_2(X_2, X3) + \ldots + f_M(X_N),$$
and I believe it should be
$$\beta_0 + f_1(X_1) + f_2(X_2) + f_3( X_3) + \ldots + f_M(X_M),$$
or even this
$$\beta_0 + f_1(X_1) +\ldots + f_M(X_M)$$
is probably sufficient.

In order to successfully install examples using Docker I did the following changes:

• There seems to be missing step which clones mli-resources GitHub repository. Perhaps RUN git clone https://github.com/h2oai/mli-resources.git should be added to Dockerfile (I cloned repo manually).
• Jupyter refuses to start under root - consider adding --allow-root parameter: `docker run -i -t -p 888

modelStudio FAQ & Troubleshooting

✨ Please, submit a new issue when dealing with potential bugs. Thanks! ✨

• Error occurred during the modelStudio() computation
• foo plot doesn't show up on the dashboard

1. Read the console output of DALEX::explain(). There could be a warning message pointing to the

• fix bibtex
• fix pytorch example
• fix installation instruction
• add tensorflow example
• link documentation
• include GIF
• add a short overview readme to the notebook directory
• write FAQ
• fix GIF text

Would suggest having a confusion matrix plot, I think we already have access to the values.

1. Values could be normalized to be represented as %ages
2. or not normalized as well. Using the computed values to draw the plot.
   if time permits one could think of some cool intuitive visualization as well.